Objective: The Internet of Things provide solutions for many societal challenges including the use of unmanned aerial vehicles to assist in emergency situations that are out of immediate reach for traditional emergency services. Out of hospital cardiac arrest (OHCA) can result in death with less than 50% of victims receiving the necessary emergency care on time. The aim of this study is to link real world heterogenous datasets to build a system to determine the difference in emergency response times when having aerial ambulance drones available compared to response times when depending solely on traditional ambulance services and lay rescuers who would use nearby publicly accessible defibrillators to treat OHCA victims. Method: The system uses the geolocations of public accessible defibrillators and ambulance services along with the times when people are likely to have a cardiac arrest to calculate response times. For comparison, a Genetic Algorithm has been developed to determine the strategic number and positions of drone bases to optimize OHCA emergency response times. Conclusion: Implementation of a nationwide aerial drone network may see significant improvements in overall emergency response times for OHCA incidents. However, the expense of implementation must be considered.

中文翻译：

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用于实现院外心脏骤停的空中救护无人机战略定位的数据驱动模拟器：遗传算法方法

目标：物联网为许多社会挑战提供了解决方案，包括使用无人驾驶飞行器来协助处理传统应急服务无法立即到达的紧急情况。院外心脏骤停 (OHCA) 可导致死亡，不到 50% 的受害者按时接受必要的紧急护理。本研究的目的是将现实世界的异构数据集联系起来，以构建一个系统，以确定与仅依赖传统救护车服务和使用附近公共可访问的非专业救援人员的响应时间相比，有空中救护无人机可用时的紧急响应时间的差异除颤器治疗 OHCA 患者。方法：该系统使用公共可访问的除颤器和救护车服务的地理位置以及人们可能发生心脏骤停的时间来计算响应时间。为了进行比较，我们开发了一种遗传算法来确定无人机基地的战略数量和位置，以优化 OHCA 应急响应时间。结论：全国空中无人机网络的实施可能会显着改善 OHCA 事件的整体应急响应时间。但是，必须考虑实施的费用。全国空中无人机网络的实施可能会显着改善 OHCA 事件的整体应急响应时间。但是，必须考虑实施费用。全国空中无人机网络的实施可能会显着改善 OHCA 事件的整体应急响应时间。但是，必须考虑实施的费用。